Design Of Commodity Futures Risk Supervision Scheme Based On Investor Psychology

In today's advanced Internet society,the application of web search engines has become an integral part of our daily lives.At the same time,the access channels for investor information have also greatly increased.Market volatility events triggered by investors' psychological biases are also increasing.Contrary to the previous lack of access to information,today's investors are in an era of information explosion,how to overcome the impact of massive information to help investors overcome common psychological biases,effectively obtain acc urate information and generate rationality in a timely manner.Market behavior is a very important research topic.Compared to the popularity of the Google Trend Index,the majority of Int ernet users in China are using Baidu's search engine.This paper selects Baidu Index's daily search data,macroeconomic indicators and investor confidence ind ex as a measure of investor's psychological substitution,and innovatively applie s it to the commodity futures market.At the same time,the daily data of a to tal of 976 trading days for a total of 15 active species from January 2,2014 to December 30,2017 were collected as the data base for empirical research,and psychological factors and macroeconomic factors for investors in the comm odity futures market were established.In the design of the decision-making scheme,this paper introduces the cla ssical AHP analytic method of decision theory,and divides the factors affectin g the historical volatility of the commodity futures market into three layers: vo latility is the target layer,Baidu index in the current and lag period,and macr oeconomic indicators.Confidence index is listed as the middle tier,which cate gorizes the common irrational behavior screening in the futures market as a hierarchy of four factors: herding,overconfidence,limited attention,and the rea ction lag.In the verification process of the scheme,the deterministic statistics,unit root test,and collinearity test were used to examine the stationarity of the sele cted indicators.Then,a panel model for establishing random effects was deter mined based on the results of the Hausman test.Macroeconomic factors were added.The significant results of the regression model for the control variables on the back panel verify the validity of the selected indicators.Then through expert surveys and questionnaire surveys,the hierarchical ma trix is assigned and the weights of each index affecting futures market risk are calculated.Finally passed the overall consistency test: the four elements namely herding effect,overconfidence,lagging response,and the limited focus on the target layer were 0.23,0.17,0.17,and 0.42 respectively,demonstrating the effe ctiveness of the program.Finally,according to the conclusions drawn from the plan,relevant policies and investment suggestions are made respectively for the futures brokerage company,the futures market supervisory institution and the in vestors themselves.